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<li class="navelem"><a class="el" href="dir_5956a3e80a20e8e03eb577bedb92689f.html">gpu</a></li><li class="navelem"><a class="el" href="dir_2be73404b46ec2282840cd36fdb9a907.html">impl</a></li>  </ul>
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<div class="title">PQScanMultiPassNoPrecomputed.cu</div>  </div>
</div><!--header-->
<div class="contents">
<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/**</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Copyright (c) Facebook, Inc. and its affiliates.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> * This source code is licensed under the MIT license found in the</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> * LICENSE file in the root directory of this source tree.</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;</div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;</div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="preprocessor">#include &quot;PQScanMultiPassNoPrecomputed.cuh&quot;</span></div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="preprocessor">#include &quot;../GpuResources.h&quot;</span></div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="preprocessor">#include &quot;PQCodeDistances.cuh&quot;</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="preprocessor">#include &quot;PQCodeLoad.cuh&quot;</span></div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="preprocessor">#include &quot;IVFUtils.cuh&quot;</span></div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="preprocessor">#include &quot;../utils/ConversionOperators.cuh&quot;</span></div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="preprocessor">#include &quot;../utils/DeviceTensor.cuh&quot;</span></div>
<div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="preprocessor">#include &quot;../utils/DeviceUtils.h&quot;</span></div>
<div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="preprocessor">#include &quot;../utils/Float16.cuh&quot;</span></div>
<div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="preprocessor">#include &quot;../utils/LoadStoreOperators.cuh&quot;</span></div>
<div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="preprocessor">#include &quot;../utils/NoTypeTensor.cuh&quot;</span></div>
<div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="preprocessor">#include &quot;../utils/StaticUtils.h&quot;</span></div>
<div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;</div>
<div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<span class="preprocessor">#include &quot;../utils/HostTensor.cuh&quot;</span></div>
<div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;</div>
<div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="keyword">namespace </span>faiss { <span class="keyword">namespace </span>gpu {</div>
<div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;</div>
<div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;<span class="comment">// This must be kept in sync with PQCodeDistances.cu</span></div>
<div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;<span class="keywordtype">bool</span> isSupportedNoPrecomputedSubDimSize(<span class="keywordtype">int</span> dims) {</div>
<div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;  <span class="keywordflow">switch</span> (dims) {</div>
<div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;    <span class="keywordflow">case</span> 1:</div>
<div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;    <span class="keywordflow">case</span> 2:</div>
<div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;    <span class="keywordflow">case</span> 3:</div>
<div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;    <span class="keywordflow">case</span> 4:</div>
<div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;    <span class="keywordflow">case</span> 6:</div>
<div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;    <span class="keywordflow">case</span> 8:</div>
<div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;    <span class="keywordflow">case</span> 10:</div>
<div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;    <span class="keywordflow">case</span> 12:</div>
<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;    <span class="keywordflow">case</span> 16:</div>
<div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;    <span class="keywordflow">case</span> 20:</div>
<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;    <span class="keywordflow">case</span> 24:</div>
<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;    <span class="keywordflow">case</span> 28:</div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;    <span class="keywordflow">case</span> 32:</div>
<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;      <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;    <span class="keywordflow">default</span>:</div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;      <span class="comment">// FIXME: larger sizes require too many registers - we need the</span></div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;      <span class="comment">// MM implementation working</span></div>
<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;      <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;  }</div>
<div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;}</div>
<div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;</div>
<div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> LookupT, <span class="keyword">typename</span> LookupVecT&gt;</div>
<div class="line"><a name="l00051"></a><span class="lineno"><a class="line" href="structfaiss_1_1gpu_1_1LoadCodeDistances.html">   51</a></span>&#160;<span class="keyword">struct </span><a class="code" href="structfaiss_1_1gpu_1_1LoadCodeDistances.html">LoadCodeDistances</a> {</div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;  <span class="keyword">static</span> <span class="keyword">inline</span> __device__ <span class="keywordtype">void</span> load(LookupT* smem,</div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;                                     LookupT* codes,</div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;                                     <span class="keywordtype">int</span> numCodes) {</div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;    constexpr <span class="keywordtype">int</span> kWordSize = <span class="keyword">sizeof</span>(LookupVecT) / <span class="keyword">sizeof</span>(LookupT);</div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;</div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;    <span class="comment">// We can only use the vector type if the data is guaranteed to be</span></div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;    <span class="comment">// aligned. The codes are innermost, so if it is evenly divisible,</span></div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;    <span class="comment">// then any slice will be aligned.</span></div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;    <span class="keywordflow">if</span> (numCodes % kWordSize == 0) {</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;      <span class="comment">// Load the data by float4 for efficiency, and then handle any remainder</span></div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;      <span class="comment">// limitVec is the number of whole vec words we can load, in terms</span></div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;      <span class="comment">// of whole blocks performing the load</span></div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;      constexpr <span class="keywordtype">int</span> kUnroll = 2;</div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;      <span class="keywordtype">int</span> limitVec = numCodes / (kUnroll * kWordSize * blockDim.x);</div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;      limitVec *= kUnroll * blockDim.x;</div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;</div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;      LookupVecT* smemV = (LookupVecT*) smem;</div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;      LookupVecT* codesV = (LookupVecT*) codes;</div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = threadIdx.x; i &lt; limitVec; i += kUnroll * blockDim.x) {</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;        LookupVecT vals[kUnroll];</div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;</div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;<span class="preprocessor"></span>        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;          vals[j] =</div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;            <a class="code" href="structfaiss_1_1gpu_1_1LoadStore.html">LoadStore&lt;LookupVecT&gt;::load</a>(&amp;codesV[i + j * blockDim.x]);</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;        }</div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;</div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;<span class="preprocessor"></span>        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;          <a class="code" href="structfaiss_1_1gpu_1_1LoadStore.html">LoadStore&lt;LookupVecT&gt;::store</a>(&amp;smemV[i + j * blockDim.x], vals[j]);</div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;        }</div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;      }</div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;      <span class="comment">// This is where we start loading the remainder that does not evenly</span></div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;      <span class="comment">// fit into kUnroll x blockDim.x</span></div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;      <span class="keywordtype">int</span> remainder = limitVec * kWordSize;</div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;</div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = remainder + threadIdx.x; i &lt; numCodes; i += blockDim.x) {</div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;        smem[i] = codes[i];</div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;      }</div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;    } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;      <span class="comment">// Potential unaligned load</span></div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;      constexpr <span class="keywordtype">int</span> kUnroll = 4;</div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;</div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;      <span class="keywordtype">int</span> limit = utils::roundDown(numCodes, kUnroll * blockDim.x);</div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;</div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;      <span class="keywordtype">int</span> i = threadIdx.x;</div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;      <span class="keywordflow">for</span> (; i &lt; limit; i += kUnroll * blockDim.x) {</div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;        LookupT vals[kUnroll];</div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;</div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;<span class="preprocessor"></span>        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;          vals[j] = codes[i + j * blockDim.x];</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;        }</div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;</div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;<span class="preprocessor"></span>        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;          smem[i + j * blockDim.x] = vals[j];</div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;        }</div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;      }</div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;      <span class="keywordflow">for</span> (; i &lt; numCodes; i += blockDim.x) {</div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;        smem[i] = codes[i];</div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;      }</div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;    }</div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;  }</div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;};</div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;</div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">int</span> NumSubQuantizers, <span class="keyword">typename</span> LookupT, <span class="keyword">typename</span> LookupVecT&gt;</div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;__global__ <span class="keywordtype">void</span></div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;pqScanNoPrecomputedMultiPass(<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;float, 2, true&gt;</a> queries,</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;                             <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;float, 3, true&gt;</a> pqCentroids,</div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;                             <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;int, 2, true&gt;</a> topQueryToCentroid,</div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;                             <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;LookupT, 4, true&gt;</a> codeDistances,</div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;                             <span class="keywordtype">void</span>** listCodes,</div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;                             <span class="keywordtype">int</span>* listLengths,</div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;                             <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;int, 2, true&gt;</a> prefixSumOffsets,</div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;                             <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor&lt;float, 1, true&gt;</a> distance) {</div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;  <span class="keyword">const</span> <span class="keyword">auto</span> codesPerSubQuantizer = pqCentroids.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(2);</div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;</div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;  <span class="comment">// Where the pq code -&gt; residual distance is stored</span></div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;  <span class="keyword">extern</span> __shared__ <span class="keywordtype">char</span> smemCodeDistances[];</div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;  LookupT* codeDist = (LookupT*) smemCodeDistances;</div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;</div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;  <span class="comment">// Each block handles a single query</span></div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;  <span class="keyword">auto</span> queryId = blockIdx.y;</div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;  <span class="keyword">auto</span> probeId = blockIdx.x;</div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;</div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;  <span class="comment">// This is where we start writing out data</span></div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;  <span class="comment">// We ensure that before the array (at offset -1), there is a 0 value</span></div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;  <span class="keywordtype">int</span> outBase = *(prefixSumOffsets[queryId][probeId].<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a50411ce4d0fa32ef715e3321b6e33212">data</a>() - 1);</div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;  <span class="keywordtype">float</span>* distanceOut = distance[outBase].<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a50411ce4d0fa32ef715e3321b6e33212">data</a>();</div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;</div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;  <span class="keyword">auto</span> listId = topQueryToCentroid[queryId][probeId];</div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;  <span class="comment">// Safety guard in case NaNs in input cause no list ID to be generated</span></div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;  <span class="keywordflow">if</span> (listId == -1) {</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;  }</div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;</div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;  <span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>* codeList = (<span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>*) listCodes[listId];</div>
<div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;  <span class="keywordtype">int</span> limit = listLengths[listId];</div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;  constexpr <span class="keywordtype">int</span> kNumCode32 = NumSubQuantizers &lt;= 4 ? 1 :</div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;    (NumSubQuantizers / 4);</div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> code32[kNumCode32];</div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> nextCode32[kNumCode32];</div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;</div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;  <span class="comment">// We double-buffer the code loading, which improves memory utilization</span></div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;  <span class="keywordflow">if</span> (threadIdx.x &lt; limit) {</div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;    LoadCode32&lt;NumSubQuantizers&gt;::load(code32, codeList, threadIdx.x);</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;  }</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;</div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;  LoadCodeDistances&lt;LookupT, LookupVecT&gt;::load(</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;    codeDist,</div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;    codeDistances[queryId][probeId].data(),</div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;    codeDistances.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(2) * codeDistances.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(3));</div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;</div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;  <span class="comment">// Prevent WAR dependencies</span></div>
<div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;  __syncthreads();</div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;</div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;  <span class="comment">// Each thread handles one code element in the list, with a</span></div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;  <span class="comment">// block-wide stride</span></div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> codeIndex = threadIdx.x;</div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;       codeIndex &lt; limit;</div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;       codeIndex += blockDim.x) {</div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;    <span class="comment">// Prefetch next codes</span></div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;    <span class="keywordflow">if</span> (codeIndex + blockDim.x &lt; limit) {</div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;      LoadCode32&lt;NumSubQuantizers&gt;::load(</div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;        nextCode32, codeList, codeIndex + blockDim.x);</div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;    }</div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;</div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;    <span class="keywordtype">float</span> dist = 0.0f;</div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;</div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;<span class="preprocessor"></span>    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> word = 0; word &lt; kNumCode32; ++word) {</div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;      constexpr <span class="keywordtype">int</span> kBytesPerCode32 =</div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;        NumSubQuantizers &lt; 4 ? NumSubQuantizers : 4;</div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;      <span class="keywordflow">if</span> (kBytesPerCode32 == 1) {</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;        <span class="keyword">auto</span> code = code32[0];</div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;        dist = ConvertTo&lt;float&gt;::to(codeDist[code]);</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;</div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;<span class="preprocessor"></span>        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> byte = 0; byte &lt; kBytesPerCode32; ++byte) {</div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;          <span class="keyword">auto</span> code = getByte(code32[word], byte * 8, 8);</div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;</div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;          <span class="keyword">auto</span> offset =</div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;            codesPerSubQuantizer * (word * kBytesPerCode32 + byte);</div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;</div>
<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;          dist += ConvertTo&lt;float&gt;::to(codeDist[offset + code]);</div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;        }</div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;      }</div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;    }</div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;</div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;    <span class="comment">// Write out intermediate distance result</span></div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;    <span class="comment">// We do not maintain indices here, in order to reduce global</span></div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;    <span class="comment">// memory traffic. Those are recovered in the final selection step.</span></div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;    distanceOut[codeIndex] = dist;</div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;</div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;    <span class="comment">// Rotate buffers</span></div>
<div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;<span class="preprocessor"></span>    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> word = 0; word &lt; kNumCode32; ++word) {</div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;      code32[word] = nextCode32[word];</div>
<div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;    }</div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;  }</div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;}</div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;</div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;<span class="keywordtype">void</span></div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;runMultiPassTile(Tensor&lt;float, 2, true&gt;&amp; queries,</div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;                 Tensor&lt;float, 2, true&gt;&amp; centroids,</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;                 Tensor&lt;float, 3, true&gt;&amp; pqCentroidsInnermostCode,</div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;                 NoTypeTensor&lt;4, true&gt;&amp; codeDistances,</div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;                 Tensor&lt;int, 2, true&gt;&amp; topQueryToCentroid,</div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;                 <span class="keywordtype">bool</span> useFloat16Lookup,</div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;                 <span class="keywordtype">int</span> bytesPerCode,</div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;                 <span class="keywordtype">int</span> numSubQuantizers,</div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;                 <span class="keywordtype">int</span> numSubQuantizerCodes,</div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;                 thrust::device_vector&lt;void*&gt;&amp; listCodes,</div>
<div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;                 thrust::device_vector&lt;void*&gt;&amp; listIndices,</div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;                 IndicesOptions indicesOptions,</div>
<div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;                 thrust::device_vector&lt;int&gt;&amp; listLengths,</div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;                 Tensor&lt;char, 1, true&gt;&amp; thrustMem,</div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;                 Tensor&lt;int, 2, true&gt;&amp; prefixSumOffsets,</div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;                 Tensor&lt;float, 1, true&gt;&amp; allDistances,</div>
<div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;                 Tensor&lt;float, 3, true&gt;&amp; heapDistances,</div>
<div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;                 Tensor&lt;int, 3, true&gt;&amp; heapIndices,</div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;                 <span class="keywordtype">int</span> k,</div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;                 Tensor&lt;float, 2, true&gt;&amp; outDistances,</div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;                 Tensor&lt;long, 2, true&gt;&amp; outIndices,</div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;                 cudaStream_t stream) {</div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;<span class="preprocessor">#ifndef FAISS_USE_FLOAT16</span></div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;<span class="preprocessor"></span>  FAISS_ASSERT(!useFloat16Lookup);</div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;<span class="preprocessor"></span></div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;  <span class="comment">// Calculate offset lengths, so we know where to write out</span></div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;  <span class="comment">// intermediate results</span></div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;  runCalcListOffsets(topQueryToCentroid, listLengths, prefixSumOffsets,</div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;                     thrustMem, stream);</div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;</div>
<div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;  <span class="comment">// Calculate residual code distances, since this is without</span></div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;  <span class="comment">// precomputed codes</span></div>
<div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;  runPQCodeDistances(pqCentroidsInnermostCode,</div>
<div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;                     queries,</div>
<div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;                     centroids,</div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;                     topQueryToCentroid,</div>
<div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;                     codeDistances,</div>
<div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;                     useFloat16Lookup,</div>
<div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;                     stream);</div>
<div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;</div>
<div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;  <span class="comment">// Convert all codes to a distance, and write out (distance,</span></div>
<div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;  <span class="comment">// index) values for all intermediate results</span></div>
<div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;  {</div>
<div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;    <span class="keyword">auto</span> kThreadsPerBlock = 256;</div>
<div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;</div>
<div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;    <span class="keyword">auto</span> grid = dim3(topQueryToCentroid.getSize(1),</div>
<div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;                     topQueryToCentroid.getSize(0));</div>
<div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;    <span class="keyword">auto</span> block = dim3(kThreadsPerBlock);</div>
<div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;</div>
<div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;    <span class="comment">// pq centroid distances</span></div>
<div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;    <span class="keyword">auto</span> smem = <span class="keyword">sizeof</span>(float);</div>
<div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;<span class="preprocessor">#ifdef FAISS_USE_FLOAT16</span></div>
<div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;<span class="preprocessor"></span>    <span class="keywordflow">if</span> (useFloat16Lookup) {</div>
<div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;      smem = <span class="keyword">sizeof</span>(half);</div>
<div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;    }</div>
<div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;<span class="preprocessor"></span>    smem *= numSubQuantizers * numSubQuantizerCodes;</div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;    FAISS_ASSERT(smem &lt;= getMaxSharedMemPerBlockCurrentDevice());</div>
<div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;</div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;<span class="preprocessor">#define RUN_PQ_OPT(NUM_SUB_Q, LOOKUP_T, LOOKUP_VEC_T)                   \</span></div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;<span class="preprocessor">    do {                                                                \</span></div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;<span class="preprocessor">      auto codeDistancesT = codeDistances.toTensor&lt;LOOKUP_T&gt;();         \</span></div>
<div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;<span class="preprocessor">                                                                        \</span></div>
<div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;<span class="preprocessor">      pqScanNoPrecomputedMultiPass&lt;NUM_SUB_Q, LOOKUP_T, LOOKUP_VEC_T&gt;   \</span></div>
<div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;<span class="preprocessor">        &lt;&lt;&lt;grid, block, smem, stream&gt;&gt;&gt;(                                \</span></div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;<span class="preprocessor">          queries,                                                      \</span></div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;<span class="preprocessor">          pqCentroidsInnermostCode,                                     \</span></div>
<div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;<span class="preprocessor">          topQueryToCentroid,                                           \</span></div>
<div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;<span class="preprocessor">          codeDistancesT,                                               \</span></div>
<div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;<span class="preprocessor">          listCodes.data().get(),                                       \</span></div>
<div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;<span class="preprocessor">          listLengths.data().get(),                                     \</span></div>
<div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;<span class="preprocessor">          prefixSumOffsets,                                             \</span></div>
<div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;<span class="preprocessor">          allDistances);                                                \</span></div>
<div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;<span class="preprocessor">    } while (0)</span></div>
<div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;<span class="preprocessor"></span></div>
<div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;<span class="preprocessor">#ifdef FAISS_USE_FLOAT16</span></div>
<div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;<span class="preprocessor"></span><span class="preprocessor">#define RUN_PQ(NUM_SUB_Q)                       \</span></div>
<div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;<span class="preprocessor">    do {                                        \</span></div>
<div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;<span class="preprocessor">      if (useFloat16Lookup) {                   \</span></div>
<div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;<span class="preprocessor">        RUN_PQ_OPT(NUM_SUB_Q, half, Half8);     \</span></div>
<div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;<span class="preprocessor">      } else {                                  \</span></div>
<div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;<span class="preprocessor">        RUN_PQ_OPT(NUM_SUB_Q, float, float4);   \</span></div>
<div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;<span class="preprocessor">      }                                         \</span></div>
<div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;<span class="preprocessor">    } while (0)</span></div>
<div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;<span class="preprocessor"></span><span class="preprocessor">#else</span></div>
<div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;<span class="preprocessor"></span><span class="preprocessor">#define RUN_PQ(NUM_SUB_Q)                       \</span></div>
<div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;<span class="preprocessor">    do {                                        \</span></div>
<div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;<span class="preprocessor">      RUN_PQ_OPT(NUM_SUB_Q, float, float4);     \</span></div>
<div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;<span class="preprocessor">    } while (0)</span></div>
<div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;<span class="preprocessor"></span><span class="preprocessor">#endif // FAISS_USE_FLOAT16</span></div>
<div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;<span class="preprocessor"></span></div>
<div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160;    <span class="keywordflow">switch</span> (bytesPerCode) {</div>
<div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;      <span class="keywordflow">case</span> 1:</div>
<div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;        RUN_PQ(1);</div>
<div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;        <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160;      <span class="keywordflow">case</span> 2:</div>
<div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;        RUN_PQ(2);</div>
<div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;        <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;      <span class="keywordflow">case</span> 3:</div>
<div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;        RUN_PQ(3);</div>
<div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;        <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;      <span class="keywordflow">case</span> 4:</div>
<div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;        RUN_PQ(4);</div>
<div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;        <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;      <span class="keywordflow">case</span> 8:</div>
<div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;        RUN_PQ(8);</div>
<div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;        <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;      <span class="keywordflow">case</span> 12:</div>
<div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160;        RUN_PQ(12);</div>
<div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;        <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;      <span class="keywordflow">case</span> 16:</div>
<div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;        RUN_PQ(16);</div>
<div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;        <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;      <span class="keywordflow">case</span> 20:</div>
<div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;        RUN_PQ(20);</div>
<div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;        <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;      <span class="keywordflow">case</span> 24:</div>
<div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;        RUN_PQ(24);</div>
<div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;        <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;      <span class="keywordflow">case</span> 28:</div>
<div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;        RUN_PQ(28);</div>
<div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;        <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;      <span class="keywordflow">case</span> 32:</div>
<div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;        RUN_PQ(32);</div>
<div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;        <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160;      <span class="keywordflow">case</span> 40:</div>
<div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;        RUN_PQ(40);</div>
<div class="line"><a name="l00350"></a><span class="lineno">  350</span>&#160;        <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;      <span class="keywordflow">case</span> 48:</div>
<div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160;        RUN_PQ(48);</div>
<div class="line"><a name="l00353"></a><span class="lineno">  353</span>&#160;        <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160;      <span class="keywordflow">case</span> 56:</div>
<div class="line"><a name="l00355"></a><span class="lineno">  355</span>&#160;        RUN_PQ(56);</div>
<div class="line"><a name="l00356"></a><span class="lineno">  356</span>&#160;        <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00357"></a><span class="lineno">  357</span>&#160;      <span class="keywordflow">case</span> 64:</div>
<div class="line"><a name="l00358"></a><span class="lineno">  358</span>&#160;        RUN_PQ(64);</div>
<div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160;        <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;      <span class="keywordflow">case</span> 96:</div>
<div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160;        RUN_PQ(96);</div>
<div class="line"><a name="l00362"></a><span class="lineno">  362</span>&#160;        <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;      <span class="keywordflow">default</span>:</div>
<div class="line"><a name="l00364"></a><span class="lineno">  364</span>&#160;        FAISS_ASSERT(<span class="keyword">false</span>);</div>
<div class="line"><a name="l00365"></a><span class="lineno">  365</span>&#160;        <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00366"></a><span class="lineno">  366</span>&#160;    }</div>
<div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160;</div>
<div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160;<span class="preprocessor">#undef RUN_PQ</span></div>
<div class="line"><a name="l00369"></a><span class="lineno">  369</span>&#160;<span class="preprocessor"></span><span class="preprocessor">#undef RUN_PQ_OPT</span></div>
<div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160;<span class="preprocessor"></span>  }</div>
<div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;</div>
<div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160;  CUDA_TEST_ERROR();</div>
<div class="line"><a name="l00373"></a><span class="lineno">  373</span>&#160;</div>
<div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160;  <span class="comment">// k-select the output in chunks, to increase parallelism</span></div>
<div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160;  runPass1SelectLists(prefixSumOffsets,</div>
<div class="line"><a name="l00376"></a><span class="lineno">  376</span>&#160;                      allDistances,</div>
<div class="line"><a name="l00377"></a><span class="lineno">  377</span>&#160;                      topQueryToCentroid.getSize(1),</div>
<div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160;                      k,</div>
<div class="line"><a name="l00379"></a><span class="lineno">  379</span>&#160;                      <span class="keyword">false</span>, <span class="comment">// L2 distance chooses smallest</span></div>
<div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;                      heapDistances,</div>
<div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160;                      heapIndices,</div>
<div class="line"><a name="l00382"></a><span class="lineno">  382</span>&#160;                      stream);</div>
<div class="line"><a name="l00383"></a><span class="lineno">  383</span>&#160;</div>
<div class="line"><a name="l00384"></a><span class="lineno">  384</span>&#160;  <span class="comment">// k-select final output</span></div>
<div class="line"><a name="l00385"></a><span class="lineno">  385</span>&#160;  <span class="keyword">auto</span> flatHeapDistances = heapDistances.downcastInner&lt;2&gt;();</div>
<div class="line"><a name="l00386"></a><span class="lineno">  386</span>&#160;  <span class="keyword">auto</span> flatHeapIndices = heapIndices.downcastInner&lt;2&gt;();</div>
<div class="line"><a name="l00387"></a><span class="lineno">  387</span>&#160;</div>
<div class="line"><a name="l00388"></a><span class="lineno">  388</span>&#160;  runPass2SelectLists(flatHeapDistances,</div>
<div class="line"><a name="l00389"></a><span class="lineno">  389</span>&#160;                      flatHeapIndices,</div>
<div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160;                      listIndices,</div>
<div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160;                      indicesOptions,</div>
<div class="line"><a name="l00392"></a><span class="lineno">  392</span>&#160;                      prefixSumOffsets,</div>
<div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160;                      topQueryToCentroid,</div>
<div class="line"><a name="l00394"></a><span class="lineno">  394</span>&#160;                      k,</div>
<div class="line"><a name="l00395"></a><span class="lineno">  395</span>&#160;                      <span class="keyword">false</span>, <span class="comment">// L2 distance chooses smallest</span></div>
<div class="line"><a name="l00396"></a><span class="lineno">  396</span>&#160;                      outDistances,</div>
<div class="line"><a name="l00397"></a><span class="lineno">  397</span>&#160;                      outIndices,</div>
<div class="line"><a name="l00398"></a><span class="lineno">  398</span>&#160;                      stream);</div>
<div class="line"><a name="l00399"></a><span class="lineno">  399</span>&#160;}</div>
<div class="line"><a name="l00400"></a><span class="lineno">  400</span>&#160;</div>
<div class="line"><a name="l00401"></a><span class="lineno">  401</span>&#160;<span class="keywordtype">void</span> runPQScanMultiPassNoPrecomputed(Tensor&lt;float, 2, true&gt;&amp; queries,</div>
<div class="line"><a name="l00402"></a><span class="lineno">  402</span>&#160;                                     Tensor&lt;float, 2, true&gt;&amp; centroids,</div>
<div class="line"><a name="l00403"></a><span class="lineno">  403</span>&#160;                                     Tensor&lt;float, 3, true&gt;&amp; pqCentroidsInnermostCode,</div>
<div class="line"><a name="l00404"></a><span class="lineno">  404</span>&#160;                                     Tensor&lt;int, 2, true&gt;&amp; topQueryToCentroid,</div>
<div class="line"><a name="l00405"></a><span class="lineno">  405</span>&#160;                                     <span class="keywordtype">bool</span> useFloat16Lookup,</div>
<div class="line"><a name="l00406"></a><span class="lineno">  406</span>&#160;                                     <span class="keywordtype">int</span> bytesPerCode,</div>
<div class="line"><a name="l00407"></a><span class="lineno">  407</span>&#160;                                     <span class="keywordtype">int</span> numSubQuantizers,</div>
<div class="line"><a name="l00408"></a><span class="lineno">  408</span>&#160;                                     <span class="keywordtype">int</span> numSubQuantizerCodes,</div>
<div class="line"><a name="l00409"></a><span class="lineno">  409</span>&#160;                                     thrust::device_vector&lt;void*&gt;&amp; listCodes,</div>
<div class="line"><a name="l00410"></a><span class="lineno">  410</span>&#160;                                     thrust::device_vector&lt;void*&gt;&amp; listIndices,</div>
<div class="line"><a name="l00411"></a><span class="lineno">  411</span>&#160;                                     IndicesOptions indicesOptions,</div>
<div class="line"><a name="l00412"></a><span class="lineno">  412</span>&#160;                                     thrust::device_vector&lt;int&gt;&amp; listLengths,</div>
<div class="line"><a name="l00413"></a><span class="lineno">  413</span>&#160;                                     <span class="keywordtype">int</span> maxListLength,</div>
<div class="line"><a name="l00414"></a><span class="lineno">  414</span>&#160;                                     <span class="keywordtype">int</span> k,</div>
<div class="line"><a name="l00415"></a><span class="lineno">  415</span>&#160;                                     <span class="comment">// output</span></div>
<div class="line"><a name="l00416"></a><span class="lineno">  416</span>&#160;                                     Tensor&lt;float, 2, true&gt;&amp; outDistances,</div>
<div class="line"><a name="l00417"></a><span class="lineno">  417</span>&#160;                                     <span class="comment">// output</span></div>
<div class="line"><a name="l00418"></a><span class="lineno">  418</span>&#160;                                     Tensor&lt;long, 2, true&gt;&amp; outIndices,</div>
<div class="line"><a name="l00419"></a><span class="lineno">  419</span>&#160;                                     GpuResources* res) {</div>
<div class="line"><a name="l00420"></a><span class="lineno">  420</span>&#160;  constexpr <span class="keywordtype">int</span> kMinQueryTileSize = 8;</div>
<div class="line"><a name="l00421"></a><span class="lineno">  421</span>&#160;  constexpr <span class="keywordtype">int</span> kMaxQueryTileSize = 128;</div>
<div class="line"><a name="l00422"></a><span class="lineno">  422</span>&#160;  constexpr <span class="keywordtype">int</span> kThrustMemSize = 16384;</div>
<div class="line"><a name="l00423"></a><span class="lineno">  423</span>&#160;</div>
<div class="line"><a name="l00424"></a><span class="lineno">  424</span>&#160;  <span class="keywordtype">int</span> nprobe = topQueryToCentroid.getSize(1);</div>
<div class="line"><a name="l00425"></a><span class="lineno">  425</span>&#160;</div>
<div class="line"><a name="l00426"></a><span class="lineno">  426</span>&#160;  <span class="keyword">auto</span>&amp; mem = res-&gt;getMemoryManagerCurrentDevice();</div>
<div class="line"><a name="l00427"></a><span class="lineno">  427</span>&#160;  <span class="keyword">auto</span> stream = res-&gt;getDefaultStreamCurrentDevice();</div>
<div class="line"><a name="l00428"></a><span class="lineno">  428</span>&#160;</div>
<div class="line"><a name="l00429"></a><span class="lineno">  429</span>&#160;  <span class="comment">// Make a reservation for Thrust to do its dirty work (global memory</span></div>
<div class="line"><a name="l00430"></a><span class="lineno">  430</span>&#160;  <span class="comment">// cross-block reduction space); hopefully this is large enough.</span></div>
<div class="line"><a name="l00431"></a><span class="lineno">  431</span>&#160;  DeviceTensor&lt;char, 1, true&gt; thrustMem1(</div>
<div class="line"><a name="l00432"></a><span class="lineno">  432</span>&#160;    mem, {kThrustMemSize}, stream);</div>
<div class="line"><a name="l00433"></a><span class="lineno">  433</span>&#160;  DeviceTensor&lt;char, 1, true&gt; thrustMem2(</div>
<div class="line"><a name="l00434"></a><span class="lineno">  434</span>&#160;    mem, {kThrustMemSize}, stream);</div>
<div class="line"><a name="l00435"></a><span class="lineno">  435</span>&#160;  DeviceTensor&lt;char, 1, true&gt;* thrustMem[2] =</div>
<div class="line"><a name="l00436"></a><span class="lineno">  436</span>&#160;    {&amp;thrustMem1, &amp;thrustMem2};</div>
<div class="line"><a name="l00437"></a><span class="lineno">  437</span>&#160;</div>
<div class="line"><a name="l00438"></a><span class="lineno">  438</span>&#160;  <span class="comment">// How much temporary storage is available?</span></div>
<div class="line"><a name="l00439"></a><span class="lineno">  439</span>&#160;  <span class="comment">// If possible, we&#39;d like to fit within the space available.</span></div>
<div class="line"><a name="l00440"></a><span class="lineno">  440</span>&#160;  <span class="keywordtype">size_t</span> sizeAvailable = mem.getSizeAvailable();</div>
<div class="line"><a name="l00441"></a><span class="lineno">  441</span>&#160;</div>
<div class="line"><a name="l00442"></a><span class="lineno">  442</span>&#160;  <span class="comment">// We run two passes of heap selection</span></div>
<div class="line"><a name="l00443"></a><span class="lineno">  443</span>&#160;  <span class="comment">// This is the size of the first-level heap passes</span></div>
<div class="line"><a name="l00444"></a><span class="lineno">  444</span>&#160;  constexpr <span class="keywordtype">int</span> kNProbeSplit = 8;</div>
<div class="line"><a name="l00445"></a><span class="lineno">  445</span>&#160;  <span class="keywordtype">int</span> pass2Chunks = std::min(nprobe, kNProbeSplit);</div>
<div class="line"><a name="l00446"></a><span class="lineno">  446</span>&#160;</div>
<div class="line"><a name="l00447"></a><span class="lineno">  447</span>&#160;  <span class="keywordtype">size_t</span> sizeForFirstSelectPass =</div>
<div class="line"><a name="l00448"></a><span class="lineno">  448</span>&#160;    pass2Chunks * k * (<span class="keyword">sizeof</span>(float) + <span class="keyword">sizeof</span>(<span class="keywordtype">int</span>));</div>
<div class="line"><a name="l00449"></a><span class="lineno">  449</span>&#160;</div>
<div class="line"><a name="l00450"></a><span class="lineno">  450</span>&#160;  <span class="comment">// How much temporary storage we need per each query</span></div>
<div class="line"><a name="l00451"></a><span class="lineno">  451</span>&#160;  <span class="keywordtype">size_t</span> sizePerQuery =</div>
<div class="line"><a name="l00452"></a><span class="lineno">  452</span>&#160;    2 * <span class="comment">// streams</span></div>
<div class="line"><a name="l00453"></a><span class="lineno">  453</span>&#160;    ((nprobe * <span class="keyword">sizeof</span>(int) + <span class="keyword">sizeof</span>(<span class="keywordtype">int</span>)) + <span class="comment">// prefixSumOffsets</span></div>
<div class="line"><a name="l00454"></a><span class="lineno">  454</span>&#160;     nprobe * maxListLength * <span class="keyword">sizeof</span>(<span class="keywordtype">float</span>) + <span class="comment">// allDistances</span></div>
<div class="line"><a name="l00455"></a><span class="lineno">  455</span>&#160;     <span class="comment">// residual distances</span></div>
<div class="line"><a name="l00456"></a><span class="lineno">  456</span>&#160;     nprobe * numSubQuantizers * numSubQuantizerCodes * <span class="keyword">sizeof</span>(float) +</div>
<div class="line"><a name="l00457"></a><span class="lineno">  457</span>&#160;     sizeForFirstSelectPass);</div>
<div class="line"><a name="l00458"></a><span class="lineno">  458</span>&#160;</div>
<div class="line"><a name="l00459"></a><span class="lineno">  459</span>&#160;  <span class="keywordtype">int</span> queryTileSize = (int) (sizeAvailable / sizePerQuery);</div>
<div class="line"><a name="l00460"></a><span class="lineno">  460</span>&#160;</div>
<div class="line"><a name="l00461"></a><span class="lineno">  461</span>&#160;  <span class="keywordflow">if</span> (queryTileSize &lt; kMinQueryTileSize) {</div>
<div class="line"><a name="l00462"></a><span class="lineno">  462</span>&#160;    queryTileSize = kMinQueryTileSize;</div>
<div class="line"><a name="l00463"></a><span class="lineno">  463</span>&#160;  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (queryTileSize &gt; kMaxQueryTileSize) {</div>
<div class="line"><a name="l00464"></a><span class="lineno">  464</span>&#160;    queryTileSize = kMaxQueryTileSize;</div>
<div class="line"><a name="l00465"></a><span class="lineno">  465</span>&#160;  }</div>
<div class="line"><a name="l00466"></a><span class="lineno">  466</span>&#160;</div>
<div class="line"><a name="l00467"></a><span class="lineno">  467</span>&#160;  <span class="comment">// FIXME: we should adjust queryTileSize to deal with this, since</span></div>
<div class="line"><a name="l00468"></a><span class="lineno">  468</span>&#160;  <span class="comment">// indexing is in int32</span></div>
<div class="line"><a name="l00469"></a><span class="lineno">  469</span>&#160;  FAISS_ASSERT(queryTileSize * nprobe * maxListLength &lt;</div>
<div class="line"><a name="l00470"></a><span class="lineno">  470</span>&#160;         std::numeric_limits&lt;int&gt;::max());</div>
<div class="line"><a name="l00471"></a><span class="lineno">  471</span>&#160;</div>
<div class="line"><a name="l00472"></a><span class="lineno">  472</span>&#160;  <span class="comment">// Temporary memory buffers</span></div>
<div class="line"><a name="l00473"></a><span class="lineno">  473</span>&#160;  <span class="comment">// Make sure there is space prior to the start which will be 0, and</span></div>
<div class="line"><a name="l00474"></a><span class="lineno">  474</span>&#160;  <span class="comment">// will handle the boundary condition without branches</span></div>
<div class="line"><a name="l00475"></a><span class="lineno">  475</span>&#160;  DeviceTensor&lt;int, 1, true&gt; prefixSumOffsetSpace1(</div>
<div class="line"><a name="l00476"></a><span class="lineno">  476</span>&#160;    mem, {queryTileSize * nprobe + 1}, stream);</div>
<div class="line"><a name="l00477"></a><span class="lineno">  477</span>&#160;  DeviceTensor&lt;int, 1, true&gt; prefixSumOffsetSpace2(</div>
<div class="line"><a name="l00478"></a><span class="lineno">  478</span>&#160;    mem, {queryTileSize * nprobe + 1}, stream);</div>
<div class="line"><a name="l00479"></a><span class="lineno">  479</span>&#160;</div>
<div class="line"><a name="l00480"></a><span class="lineno">  480</span>&#160;  DeviceTensor&lt;int, 2, true&gt; prefixSumOffsets1(</div>
<div class="line"><a name="l00481"></a><span class="lineno">  481</span>&#160;    prefixSumOffsetSpace1[1].data(),</div>
<div class="line"><a name="l00482"></a><span class="lineno">  482</span>&#160;    {queryTileSize, nprobe});</div>
<div class="line"><a name="l00483"></a><span class="lineno">  483</span>&#160;  DeviceTensor&lt;int, 2, true&gt; prefixSumOffsets2(</div>
<div class="line"><a name="l00484"></a><span class="lineno">  484</span>&#160;    prefixSumOffsetSpace2[1].data(),</div>
<div class="line"><a name="l00485"></a><span class="lineno">  485</span>&#160;    {queryTileSize, nprobe});</div>
<div class="line"><a name="l00486"></a><span class="lineno">  486</span>&#160;  DeviceTensor&lt;int, 2, true&gt;* prefixSumOffsets[2] =</div>
<div class="line"><a name="l00487"></a><span class="lineno">  487</span>&#160;    {&amp;prefixSumOffsets1, &amp;prefixSumOffsets2};</div>
<div class="line"><a name="l00488"></a><span class="lineno">  488</span>&#160;</div>
<div class="line"><a name="l00489"></a><span class="lineno">  489</span>&#160;  <span class="comment">// Make sure the element before prefixSumOffsets is 0, since we</span></div>
<div class="line"><a name="l00490"></a><span class="lineno">  490</span>&#160;  <span class="comment">// depend upon simple, boundary-less indexing to get proper results</span></div>
<div class="line"><a name="l00491"></a><span class="lineno">  491</span>&#160;  CUDA_VERIFY(cudaMemsetAsync(prefixSumOffsetSpace1.data(),</div>
<div class="line"><a name="l00492"></a><span class="lineno">  492</span>&#160;                              0,</div>
<div class="line"><a name="l00493"></a><span class="lineno">  493</span>&#160;                              <span class="keyword">sizeof</span>(int),</div>
<div class="line"><a name="l00494"></a><span class="lineno">  494</span>&#160;                              stream));</div>
<div class="line"><a name="l00495"></a><span class="lineno">  495</span>&#160;  CUDA_VERIFY(cudaMemsetAsync(prefixSumOffsetSpace2.data(),</div>
<div class="line"><a name="l00496"></a><span class="lineno">  496</span>&#160;                              0,</div>
<div class="line"><a name="l00497"></a><span class="lineno">  497</span>&#160;                              <span class="keyword">sizeof</span>(int),</div>
<div class="line"><a name="l00498"></a><span class="lineno">  498</span>&#160;                              stream));</div>
<div class="line"><a name="l00499"></a><span class="lineno">  499</span>&#160;</div>
<div class="line"><a name="l00500"></a><span class="lineno">  500</span>&#160;  <span class="keywordtype">int</span> codeDistanceTypeSize = <span class="keyword">sizeof</span>(float);</div>
<div class="line"><a name="l00501"></a><span class="lineno">  501</span>&#160;<span class="preprocessor">#ifdef FAISS_USE_FLOAT16</span></div>
<div class="line"><a name="l00502"></a><span class="lineno">  502</span>&#160;<span class="preprocessor"></span>  <span class="keywordflow">if</span> (useFloat16Lookup) {</div>
<div class="line"><a name="l00503"></a><span class="lineno">  503</span>&#160;    codeDistanceTypeSize = <span class="keyword">sizeof</span>(half);</div>
<div class="line"><a name="l00504"></a><span class="lineno">  504</span>&#160;  }</div>
<div class="line"><a name="l00505"></a><span class="lineno">  505</span>&#160;<span class="preprocessor">#else</span></div>
<div class="line"><a name="l00506"></a><span class="lineno">  506</span>&#160;<span class="preprocessor"></span>  FAISS_ASSERT(!useFloat16Lookup);</div>
<div class="line"><a name="l00507"></a><span class="lineno">  507</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00508"></a><span class="lineno">  508</span>&#160;<span class="preprocessor"></span></div>
<div class="line"><a name="l00509"></a><span class="lineno">  509</span>&#160;  <span class="keywordtype">int</span> totalCodeDistancesSize =</div>
<div class="line"><a name="l00510"></a><span class="lineno">  510</span>&#160;    queryTileSize * nprobe * numSubQuantizers * numSubQuantizerCodes *</div>
<div class="line"><a name="l00511"></a><span class="lineno">  511</span>&#160;    codeDistanceTypeSize;</div>
<div class="line"><a name="l00512"></a><span class="lineno">  512</span>&#160;</div>
<div class="line"><a name="l00513"></a><span class="lineno">  513</span>&#160;  DeviceTensor&lt;char, 1, true&gt; codeDistances1Mem(</div>
<div class="line"><a name="l00514"></a><span class="lineno">  514</span>&#160;    mem, {totalCodeDistancesSize}, stream);</div>
<div class="line"><a name="l00515"></a><span class="lineno">  515</span>&#160;  NoTypeTensor&lt;4, true&gt; codeDistances1(</div>
<div class="line"><a name="l00516"></a><span class="lineno">  516</span>&#160;    codeDistances1Mem.data(),</div>
<div class="line"><a name="l00517"></a><span class="lineno">  517</span>&#160;    codeDistanceTypeSize,</div>
<div class="line"><a name="l00518"></a><span class="lineno">  518</span>&#160;    {queryTileSize, nprobe, numSubQuantizers, numSubQuantizerCodes});</div>
<div class="line"><a name="l00519"></a><span class="lineno">  519</span>&#160;</div>
<div class="line"><a name="l00520"></a><span class="lineno">  520</span>&#160;  DeviceTensor&lt;char, 1, true&gt; codeDistances2Mem(</div>
<div class="line"><a name="l00521"></a><span class="lineno">  521</span>&#160;    mem, {totalCodeDistancesSize}, stream);</div>
<div class="line"><a name="l00522"></a><span class="lineno">  522</span>&#160;  NoTypeTensor&lt;4, true&gt; codeDistances2(</div>
<div class="line"><a name="l00523"></a><span class="lineno">  523</span>&#160;    codeDistances2Mem.data(),</div>
<div class="line"><a name="l00524"></a><span class="lineno">  524</span>&#160;    codeDistanceTypeSize,</div>
<div class="line"><a name="l00525"></a><span class="lineno">  525</span>&#160;    {queryTileSize, nprobe, numSubQuantizers, numSubQuantizerCodes});</div>
<div class="line"><a name="l00526"></a><span class="lineno">  526</span>&#160;</div>
<div class="line"><a name="l00527"></a><span class="lineno">  527</span>&#160;  NoTypeTensor&lt;4, true&gt;* codeDistances[2] =</div>
<div class="line"><a name="l00528"></a><span class="lineno">  528</span>&#160;    {&amp;codeDistances1, &amp;codeDistances2};</div>
<div class="line"><a name="l00529"></a><span class="lineno">  529</span>&#160;</div>
<div class="line"><a name="l00530"></a><span class="lineno">  530</span>&#160;  DeviceTensor&lt;float, 1, true&gt; allDistances1(</div>
<div class="line"><a name="l00531"></a><span class="lineno">  531</span>&#160;    mem, {queryTileSize * nprobe * maxListLength}, stream);</div>
<div class="line"><a name="l00532"></a><span class="lineno">  532</span>&#160;  DeviceTensor&lt;float, 1, true&gt; allDistances2(</div>
<div class="line"><a name="l00533"></a><span class="lineno">  533</span>&#160;    mem, {queryTileSize * nprobe * maxListLength}, stream);</div>
<div class="line"><a name="l00534"></a><span class="lineno">  534</span>&#160;  DeviceTensor&lt;float, 1, true&gt;* allDistances[2] =</div>
<div class="line"><a name="l00535"></a><span class="lineno">  535</span>&#160;    {&amp;allDistances1, &amp;allDistances2};</div>
<div class="line"><a name="l00536"></a><span class="lineno">  536</span>&#160;</div>
<div class="line"><a name="l00537"></a><span class="lineno">  537</span>&#160;  DeviceTensor&lt;float, 3, true&gt; heapDistances1(</div>
<div class="line"><a name="l00538"></a><span class="lineno">  538</span>&#160;    mem, {queryTileSize, pass2Chunks, k}, stream);</div>
<div class="line"><a name="l00539"></a><span class="lineno">  539</span>&#160;  DeviceTensor&lt;float, 3, true&gt; heapDistances2(</div>
<div class="line"><a name="l00540"></a><span class="lineno">  540</span>&#160;    mem, {queryTileSize, pass2Chunks, k}, stream);</div>
<div class="line"><a name="l00541"></a><span class="lineno">  541</span>&#160;  DeviceTensor&lt;float, 3, true&gt;* heapDistances[2] =</div>
<div class="line"><a name="l00542"></a><span class="lineno">  542</span>&#160;    {&amp;heapDistances1, &amp;heapDistances2};</div>
<div class="line"><a name="l00543"></a><span class="lineno">  543</span>&#160;</div>
<div class="line"><a name="l00544"></a><span class="lineno">  544</span>&#160;  DeviceTensor&lt;int, 3, true&gt; heapIndices1(</div>
<div class="line"><a name="l00545"></a><span class="lineno">  545</span>&#160;    mem, {queryTileSize, pass2Chunks, k}, stream);</div>
<div class="line"><a name="l00546"></a><span class="lineno">  546</span>&#160;  DeviceTensor&lt;int, 3, true&gt; heapIndices2(</div>
<div class="line"><a name="l00547"></a><span class="lineno">  547</span>&#160;    mem, {queryTileSize, pass2Chunks, k}, stream);</div>
<div class="line"><a name="l00548"></a><span class="lineno">  548</span>&#160;  DeviceTensor&lt;int, 3, true&gt;* heapIndices[2] =</div>
<div class="line"><a name="l00549"></a><span class="lineno">  549</span>&#160;    {&amp;heapIndices1, &amp;heapIndices2};</div>
<div class="line"><a name="l00550"></a><span class="lineno">  550</span>&#160;</div>
<div class="line"><a name="l00551"></a><span class="lineno">  551</span>&#160;  <span class="keyword">auto</span> streams = res-&gt;getAlternateStreamsCurrentDevice();</div>
<div class="line"><a name="l00552"></a><span class="lineno">  552</span>&#160;  streamWait(streams, {stream});</div>
<div class="line"><a name="l00553"></a><span class="lineno">  553</span>&#160;</div>
<div class="line"><a name="l00554"></a><span class="lineno">  554</span>&#160;  <span class="keywordtype">int</span> curStream = 0;</div>
<div class="line"><a name="l00555"></a><span class="lineno">  555</span>&#160;</div>
<div class="line"><a name="l00556"></a><span class="lineno">  556</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> query = 0; query &lt; queries.getSize(0); query += queryTileSize) {</div>
<div class="line"><a name="l00557"></a><span class="lineno">  557</span>&#160;    <span class="keywordtype">int</span> numQueriesInTile =</div>
<div class="line"><a name="l00558"></a><span class="lineno">  558</span>&#160;      std::min(queryTileSize, queries.getSize(0) - query);</div>
<div class="line"><a name="l00559"></a><span class="lineno">  559</span>&#160;</div>
<div class="line"><a name="l00560"></a><span class="lineno">  560</span>&#160;    <span class="keyword">auto</span> prefixSumOffsetsView =</div>
<div class="line"><a name="l00561"></a><span class="lineno">  561</span>&#160;      prefixSumOffsets[curStream]-&gt;narrowOutermost(0, numQueriesInTile);</div>
<div class="line"><a name="l00562"></a><span class="lineno">  562</span>&#160;</div>
<div class="line"><a name="l00563"></a><span class="lineno">  563</span>&#160;    <span class="keyword">auto</span> codeDistancesView =</div>
<div class="line"><a name="l00564"></a><span class="lineno">  564</span>&#160;      codeDistances[curStream]-&gt;narrowOutermost(0, numQueriesInTile);</div>
<div class="line"><a name="l00565"></a><span class="lineno">  565</span>&#160;    <span class="keyword">auto</span> coarseIndicesView =</div>
<div class="line"><a name="l00566"></a><span class="lineno">  566</span>&#160;      topQueryToCentroid.narrowOutermost(query, numQueriesInTile);</div>
<div class="line"><a name="l00567"></a><span class="lineno">  567</span>&#160;    <span class="keyword">auto</span> queryView =</div>
<div class="line"><a name="l00568"></a><span class="lineno">  568</span>&#160;      queries.narrowOutermost(query, numQueriesInTile);</div>
<div class="line"><a name="l00569"></a><span class="lineno">  569</span>&#160;</div>
<div class="line"><a name="l00570"></a><span class="lineno">  570</span>&#160;    <span class="keyword">auto</span> heapDistancesView =</div>
<div class="line"><a name="l00571"></a><span class="lineno">  571</span>&#160;      heapDistances[curStream]-&gt;narrowOutermost(0, numQueriesInTile);</div>
<div class="line"><a name="l00572"></a><span class="lineno">  572</span>&#160;    <span class="keyword">auto</span> heapIndicesView =</div>
<div class="line"><a name="l00573"></a><span class="lineno">  573</span>&#160;      heapIndices[curStream]-&gt;narrowOutermost(0, numQueriesInTile);</div>
<div class="line"><a name="l00574"></a><span class="lineno">  574</span>&#160;</div>
<div class="line"><a name="l00575"></a><span class="lineno">  575</span>&#160;    <span class="keyword">auto</span> outDistanceView =</div>
<div class="line"><a name="l00576"></a><span class="lineno">  576</span>&#160;      outDistances.narrowOutermost(query, numQueriesInTile);</div>
<div class="line"><a name="l00577"></a><span class="lineno">  577</span>&#160;    <span class="keyword">auto</span> outIndicesView =</div>
<div class="line"><a name="l00578"></a><span class="lineno">  578</span>&#160;      outIndices.narrowOutermost(query, numQueriesInTile);</div>
<div class="line"><a name="l00579"></a><span class="lineno">  579</span>&#160;</div>
<div class="line"><a name="l00580"></a><span class="lineno">  580</span>&#160;    runMultiPassTile(queryView,</div>
<div class="line"><a name="l00581"></a><span class="lineno">  581</span>&#160;                     centroids,</div>
<div class="line"><a name="l00582"></a><span class="lineno">  582</span>&#160;                     pqCentroidsInnermostCode,</div>
<div class="line"><a name="l00583"></a><span class="lineno">  583</span>&#160;                     codeDistancesView,</div>
<div class="line"><a name="l00584"></a><span class="lineno">  584</span>&#160;                     coarseIndicesView,</div>
<div class="line"><a name="l00585"></a><span class="lineno">  585</span>&#160;                     useFloat16Lookup,</div>
<div class="line"><a name="l00586"></a><span class="lineno">  586</span>&#160;                     bytesPerCode,</div>
<div class="line"><a name="l00587"></a><span class="lineno">  587</span>&#160;                     numSubQuantizers,</div>
<div class="line"><a name="l00588"></a><span class="lineno">  588</span>&#160;                     numSubQuantizerCodes,</div>
<div class="line"><a name="l00589"></a><span class="lineno">  589</span>&#160;                     listCodes,</div>
<div class="line"><a name="l00590"></a><span class="lineno">  590</span>&#160;                     listIndices,</div>
<div class="line"><a name="l00591"></a><span class="lineno">  591</span>&#160;                     indicesOptions,</div>
<div class="line"><a name="l00592"></a><span class="lineno">  592</span>&#160;                     listLengths,</div>
<div class="line"><a name="l00593"></a><span class="lineno">  593</span>&#160;                     *thrustMem[curStream],</div>
<div class="line"><a name="l00594"></a><span class="lineno">  594</span>&#160;                     prefixSumOffsetsView,</div>
<div class="line"><a name="l00595"></a><span class="lineno">  595</span>&#160;                     *allDistances[curStream],</div>
<div class="line"><a name="l00596"></a><span class="lineno">  596</span>&#160;                     heapDistancesView,</div>
<div class="line"><a name="l00597"></a><span class="lineno">  597</span>&#160;                     heapIndicesView,</div>
<div class="line"><a name="l00598"></a><span class="lineno">  598</span>&#160;                     k,</div>
<div class="line"><a name="l00599"></a><span class="lineno">  599</span>&#160;                     outDistanceView,</div>
<div class="line"><a name="l00600"></a><span class="lineno">  600</span>&#160;                     outIndicesView,</div>
<div class="line"><a name="l00601"></a><span class="lineno">  601</span>&#160;                     streams[curStream]);</div>
<div class="line"><a name="l00602"></a><span class="lineno">  602</span>&#160;</div>
<div class="line"><a name="l00603"></a><span class="lineno">  603</span>&#160;    curStream = (curStream + 1) % 2;</div>
<div class="line"><a name="l00604"></a><span class="lineno">  604</span>&#160;  }</div>
<div class="line"><a name="l00605"></a><span class="lineno">  605</span>&#160;</div>
<div class="line"><a name="l00606"></a><span class="lineno">  606</span>&#160;  streamWait({stream}, streams);</div>
<div class="line"><a name="l00607"></a><span class="lineno">  607</span>&#160;}</div>
<div class="line"><a name="l00608"></a><span class="lineno">  608</span>&#160;</div>
<div class="line"><a name="l00609"></a><span class="lineno">  609</span>&#160;} } <span class="comment">// namespace</span></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html">faiss::gpu::Tensor</a></div><div class="ttdoc">Our tensor type. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00028">Tensor.cuh:28</a></div></div>
<div class="ttc" id="structfaiss_1_1gpu_1_1LoadCodeDistances_html"><div class="ttname"><a href="structfaiss_1_1gpu_1_1LoadCodeDistances.html">faiss::gpu::LoadCodeDistances</a></div><div class="ttdef"><b>Definition:</b> <a href="PQScanMultiPassNoPrecomputed_8cu_source.html#l00051">PQScanMultiPassNoPrecomputed.cu:51</a></div></div>
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